LLM-Based NLP System Architecture

Budget: $25 - $50/hr

I’m planning a new natural-language-processing platform powered by large language models and I need an experienced AI architect to lay down a solid, future-proof technical blueprint. Your role is purely architectural—you won’t be asked to train or fine-tune models right now, but you will decide how every component should fit together so that development can move ahead smoothly once the plan is approved.

Here’s what I’m expecting to receive from you:

• A complete system architecture diagram (high-level and detailed views) highlighting data flow, model hosting, orchestration, and integration touch-points with existing services and APIs. • Technology stack recommendations covering model serving frameworks (e.g., Hugging Face, Vertex AI, Azure OpenAI), vector databases, message queues, monitoring, and CI/CD tooling. • A data lifecycle plan that spells out ingestion, cleansing, storage, controls, and compliance considerations. • Scaling and cost-optimisation guidelines, including GPU/CPU requirements and a roadmap for moving from prototype to production. • Security and governance notes—role-based access, secrets management, and audit logging. • A rollout strategy with clear milestones so internal teams know exactly how to implement what you design.

If you have prior experience architecting LLM-centric NLP solutions in the cloud (AWS, GCP, or Azure), please mention the real-world challenges you solved. Diagrams can be delivered in Draw.io, Lucidchart, or another clear visual format alongside a concise written rationale (PDF or Markdown).

I’m ready to start as soon as I find the right fit and will be available to clarify domain specifics and legacy system constraints whenever needed.